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MTL-afroxlmr-finetuned
tadiecool29/MTL-afroxlmr-finetuned
MTL-afroxlmr-finetuned is a machine learning model from tadiecool29. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Aug 30, 2026
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At a glance
- Library
- transformers
- License
- mit
- Access
- Public
- Created
- Aug 30, 2026
- Updated
- Aug 30, 2026
- SHA
- bed91750
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
MTL-afroxlmr-finetuned
This model is a fine-tuned version of Davlan/afro-xlmr-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5548
- Stance F1: 0.7328
- Sentiment F1: 0.7262
- F1: 0.7295
- Stance Acc: 0.7259
- Sentiment Acc: 0.7309
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 300
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Stance F1 | Sentiment F1 | F1 | Stance Acc | Sentiment Acc |
|---|---|---|---|---|---|---|---|---|
| 1.8039 | 1.0 | 377 | 1.5518 | 0.6676 | 0.6854 | 0.6765 | 0.6633 | 0.6895 |
| 1.3935 | 2.0 | 754 | 1.3830 | 0.7123 | 0.7081 | 0.7102 | 0.7082 | 0.7182 |
| 1.2098 | 3.0 | 1131 | 1.3901 | 0.7216 | 0.7139 | 0.7177 | 0.7145 | 0.7232 |
| 1.0428 | 4.0 | 1508 | 1.4242 | 0.7272 | 0.7231 | 0.7252 | 0.7195 | 0.7232 |
| 0.8773 | 5.0 | 1885 | 1.4457 | 0.7365 | 0.7213 | 0.7289 | 0.7307 | 0.7257 |
| 0.7568 | 6.0 | 2262 | 1.5007 | 0.7311 | 0.7161 | 0.7236 | 0.7232 | 0.7207 |
| 0.7301 | 7.0 | 2639 | 1.5200 | 0.7379 | 0.7179 | 0.7279 | 0.7294 | 0.7219 |
| 0.7132 | 8.0 | 3016 | 1.5382 | 0.7420 | 0.7185 | 0.7303 | 0.7344 | 0.7219 |
| 0.6182 | 9.0 | 3393 | 1.5581 | 0.7457 | 0.7151 | 0.7304 | 0.7382 | 0.7182 |
| 0.6430 | 10.0 | 3770 | 1.5557 | 0.7421 | 0.7122 | 0.7271 | 0.7344 | 0.7157 |
Framework versions
- Transformers 5.15.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- License
- mit
- Created
- Aug 30, 2026
- Updated
- Aug 30, 2026